Forecasting is an art of saying what will happen and explaining if it doesn’t. Undeniably a good sales forecasting technique is the plight of most sales leaders. It is a critical business function for every company and one needs to do it right. The methodologies used need to continually evolve with the business to have a perfect match. But sales forecasting templates aren’t a free size t-shirt that can be used by everybody. You need to get the size right, you need to customize it to your comfort carefully and update it from time to time to be in control. Where does one start that? We’ll discuss it all here.

Get the basics right

I once read an article in Forbes which stated the 4 basic principles for a great sales forecast and I couldn’t agree more. Dive into this article for a detailed explanation. Nevertheless, the 4 golden principles are as follows:

Good forecasting requires a good sales strategy

Good forecasting requires an understanding of your buyer’s behavior

Good forecasting requires a milestone-driven pipeline process

Good forecasting requires continual improvement

Show me the data

Tracking the sales data is the most important chapter of this syllabus. Understanding which sales strategies worked the best and worst, the performances of your various marketing channels, campaigns and sales personnel give you a hawk eye view. How do you do that? Well from small spread sheets to data heavy dashboards can be employed to your service based on what and how much data your business generates. There are plenty of ready made templates available online to choose for your business. This would give you a definite head start.

Market intelligence and pipelining

A sales pipeline can be of great value to sales folks by providing a structured strategy for turning qualified leads into repeat customers. This in turn benefits the forecasting. The key here is to generate insights from each level of your pipeline and improve the accuracy of your forecast. Study the market trend well, derive insights and extrapolate where relevant. A mix and match of these techniques will get you up and steady.

Evolution

A continuous process of improvement is the need of the hour. Your business evolves, your customers evolve and so does the sales trend. Similarly, the forecasting should run under a continuous improvement program. Follow up on errors and inaccuracies, monitor the deviations and tweak your forecasting methods from time to time.

“If you have reason to think that yesterday’s forecast went wrong, there is no glory in sticking to it.” ~Nate Silver

You may employ regular statistical techniques or machine learning algos for forecasting but how it impacts your business is the main catch. Prediction systems are changing the face of businesses and this is how you build it right. Seemed pretty interesting eh? Wait there’s more.

To get a taste of building prediction systems in F&B industry we bring to you #buildwithAWS where you learn, understand and build a simple system that uses Machine Learning Models to predict the sales and inventory of a Restaurant for a start. limited entries only. Don’t wait up, apply now to get a seat!

Written By

| Small town guy, big dreams | Wandering wordsmith with a thousand stories to tell and listen, tell me yours? |
| Foodaholic, foodpornographer, loves cooking and feeding people | Digital marketer | Talented enough to roll out a captivating blog, infographic, eDM or stuff that people will actually read |
| Human by birth, engineer by education, Data Scientist by profession and a Musician by passion | In God I trust, rest all must bring data |

About Author

Pratik Saurav

| Small town guy, big dreams | Wandering wordsmith with a thousand stories to tell and listen, tell me yours? |
| Foodaholic, foodpornographer, loves cooking and feeding people | Digital marketer | Talented enough to roll out a captivating blog, infographic, eDM or stuff that people will actually read |
| Human by birth, engineer by education, Data Scientist by profession and a Musician by passion | In God I trust, rest all must bring data |